Differences in Data

Have you ever been pre-judged by someone before they had a chance to really get to know you? When I look at where data-sets are today, that’s kind of how I feel. We are taking our best guest at personifying individuals based on a series of various data sets that semi-fit together. In our last blog we talked about the importance of content personalization. If we are going to get there, data interpretation is just as important as the data collected about a person.

Different Types of Data

Qualitative vs. Quantitative

The biggest distinction in reading quantitative vs. qualitative data, is whether something can be easily categorized or not. Quantitative data is data that can be categorized numerically. Your shoe size, your height, your income, your zipcode etc. etc. In other words, it’s the demographic information that can be easily collected.. Qualitative data, however, cannot be categorized numerically. In the words of Isaac Newton, “every action causes a reaction”. This reaction, or emotional response can be classified as qualitative data.  

Target, for example, takes to the twitter-world to see the emotional reactions to new product launches. They collect this qualitative data about the individual responses to better understand their customers and move one step closer towards content personalization.

These two data sets go hand-in-hand because you can infer many correlations such as, location eludes towards cultural responses, affluence levels indicate certain buyer behavior, and so on.

First Party Data

Finders keepers! Anything you collect about your customer, is yours to keep. This means your brand gets the first glimpse into your customer’s interaction with your brand. First Party Data is one of the most valuable data sets because you can deploy any data aggregation strategy to understand the exact relationship between you and your customer during the buying journey.

For example, if you want insight into how your customers interact with your website, deploying a heat-mapping strategy to collect data on what images individuals click on might be the best route for gathering this first-hand intel.

Second Party Data

Second party data is like the ultimate tease. A customer may be in a data relationship with someone else, but you’re still benefitting from that relationship. For example, a customer releases the rights for Google AdWords to track their search history but you’re still benefitting from that same relationship with AdWords. It’s common for brands to strategically partner in a data sharing strategy to obtain information that otherwise might be too costly to collect on their own. This is why second party data becomes valuable, and knowing what data you’d need to further complete the personalization puzzle will help define the strategic partnerships you can create.

Third Party Data

This data is the most widely adopted data collection strategy. Marketers depend on data collectors to aggregate intel on customers that they can use to develop a variation of marketing strategies. Unfortunately for third-party data, it’s becoming less common in strategy development as marketers want more first-hand insight aka. first party data.

Knowing what type of data you are collection, can help you figure out what pieces of data are missing that will help you complete the puzzle towards content personalization.

References:

http://www.huffingtonpost.com/advertising-week/turning-intentions-into-c_b_8137128.html

http://www.getelastic.com/beyond-product-recommendations-big-datas-role-in-personalization/

http://www.b2bmarketinginsider.com/strategy/are-you-using-first-party-data-to-drive-personalized-customer-experience

http://www.emarketer.com/Article/Marketers-Put-First-Party-Data-First/1012663

http://marketingland.com/can-marketers-find-best-customer-data-noses-139308

http://marketingland.com/second-party-data-digital-marketers-128254

http://www.signal.co/blog/data-sharing-second-party-data/

Personalization is The New Nirvana

Digital marketing, such as advertisements, we see are like works of art. Creative directors are tasked with composing a variety of elements from realism to sound composition, to developing an advertisement that will grab your attention, keeping your interest, instilling desire, and demanding action. The difference between art and advertising, is art is meant to be enjoyable, whereas an advertisement is meant to fulfill a monetary purpose. In today’s digital world, creating advertisements can get even more complex, such as adding in a layer of augmented reality, that will engulf the targeted customer into an entire experience. The problem creative directors have, is to build multiple works of art that will appeal to a variety of different personalities to drive the same end goal.

Using Data to Develop Marketing Content

True personalization is creating a group segment audience of 1. This is also known as ‘nirvana’. The challenge that presents itself here is that no two individuals are alike. Even the most extreme identical twins have a small degree of variation in their personalities. I want to talk about a concept that I like to call ‘Deep Data’. I want to differentiate this from Big Data, because I think Deep Data as a descriptor to determine a person’s psyche.

There are plenty of Big Data sources available to help creative directors build ads based on high-level segmentation. Understanding demographics, can help creative directors determine basic cultural differences, and develop advertisements that will fit in various markets. Where it starts to become tricky, is gathering the deep data sources. It’s much easier to figure out where someone lives vs. the emotional intelligence of that individual. The other challenge, is most people are willing to give up demographical information, but any info that would be seen as compromising to the person is much harder to attain.

This is where digital trust is crucial if we want to progress towards true personalization.

Gathering Deep Data

Between beacons, IP addresses, learning algorithms, cookies and surveys there are plenty of strategic ways to gather information about a person. The problem, is all this data gets collected and stored in various systems and there isn’t a current solution that combines them all into one. The other issue presented here, is tracking the success of individual campaigns. There are ways to track open rates, impressions, click through’s and conversions, but what this data doesn’t tell you, is why an ad didn’t work with those that didn’t convert, and why it worked with those that did.

As we move towards Nirvana, creative directors and marketers will need to be able to understand each individual and know exactly which mixtures of messages and content will create the efficacy that every business wants without losing the consumer’s trust.

References:

http://www.forbes.com/sites/sap/2015/07/11/marketing-nirvana-engaging-with-an-audience-of-one/

http://searchcontentmanagement.techtarget.com/feature/Location-data-adds-context-for-Web-personalization

http://www.forbes.com/sites/johnrampton/2015/09/03/better-data-enables-better-customer-segmentation/

http://www.martechadvisor.com/marketing-analytics/clickagy-launches-data-driven-content-providing-intelligent-on-page-optimization-using-audience-profiles/

http://www.dtcperspectives.com/getting-to-the-how-unlocking-identification-personalization-and-the-regulatory-landscape/

It’s Getting Personal

I’ve been reading many articles on data personalization as it relates to content marketing and I keep arriving at the same conclusion – It’s all about the story. But what story are we actually telling? A person doesn’t just have one story, they have multiple stories. Trying to reach someone when they want to be reached can get tricky. Are we appealing to them when they are working? Or do we try to reach them at home? These are questions data is hoping to help answer.

The B2B Story

You arrive at the office and you’re immediately bombarded with emails that never seem to end. You get called into your morning meetings where someone in the room is trying to ‘sell’ something – an idea, a campaign, a new tool that the company should buy, etc… Before you know it, it’s time for lunch. While at lunch you login to Linkedin and you’re flooded with even more ads – new job offerings, new services, new startups, etc…

Remember the famous quote: “It’s not personal, it’s just business?” While reading an article on B2B content personalization, the core message became clear; before you waste precious time on that powerpoint, find out how your boss wants information delivered. Marketers are presented with the same challenge. When creating the B2B message – find out exactly how the target audience wants information delivered. This will save you ample amounts of time in delivering the right message at the right time to the right person, because after all… time is money.

The B2C Story

You get off of work, and now you’re just an ordinary consumer faced with an amplified amount of places or things to spend your hard earned money. In our last blog, we talked about the importance of data personalization and why consumers want individualized messages, so it resonates as an emotional and relevant message.

If you aren’t familiar with Simon Sinek, he is famous for his Ted Talk on the ‘What’ vs. ‘Why’. He explains the seduction involved in storytelling and describes the brilliance behind Apple’s marketing messaging. Where Apple has the competitive edge over many businesses from access to their unique data asset. They understand their consumers so well, that their messages dig deep to connect with who they are… because ‘It’s all about me”.

The Differences in Constructing the Story

There are two main differences in B2B and B2C data. B2B data is more quantitative or objective in purpose, so it is typically used for lead generation. B2C data is more qualitative or subjective and help marketers piece together profiles to understand who you are, so there is more of an emotional connection. The ultimate goal in marketing, would be one-on-one, aka. personalization. When constructing these stories, it’s important to remember that people don’t become an entirely different person when they bounce from their B2B to B2C roles. To gather all of these puzzle pieces, it’s either ridiculously expensive or the data sets are very jumbled. The solution would be to have a robust platform enabling marketers the flexibility to select the correct data sources to construct the compelling marketing messages that they can apply to their target audience, at the times in which they would like to be reached.

Data still has a far road ahead for marketers to reach personalization, but we are slowly crossing the chasm to deliver the optimal value for their end customers.

 

Resources:

http://m.bizcommunity.com/Article.aspx?l=196&c=423&i=132915

http://techcrunch.com/2015/08/14/the-future-of-consumer-marketing-is-personal-2/?utm_medium=referral&utm_source=pulsenews

http://www.business2community.com/b2b-marketing/b2b-personalization-is-still-far-from-wash-rinse-repeat-mode-but-you-can-create-the-right-framework-01280978

Data Personalization

Hi- I’m Fabrice, the Founder and CEO of Diggen. I live in Southern California, but grew up on the East Coast. I’m largely passionate about startups, technology, and a big foodie. So why does this information matter? What’s the point of me giving you an inside look into who I am? Simple. Data Personalization.

The Purpose of Personalizing

Do you prefer these black shoes or those blue shoes? Do you want to be bothered in the morning, or in the evening? In my brief description above, you only learned a few things. I didn’t tell you what types of food I like. I didn’t share where in Southern California I live. Since consumers are complex, the software needs to be as equally complex. As a marketer- it’s your goal to create real-time personalized experiences for consumers, without coming off as creepy. Ultimately creating more relevancy for each consumer, so they become more engaged.

The Problem with Personalization

Consumers are complex. Because there are so many facets to a person, it makes it challenging to know exactly what they are thinking. Our industry has done a horrible job protecting the consumer and establishing digital trust. As a result, consumers are reluctant to release anything about themselves and we, the marketers, end up spending a ton of money on AB testing just to figure out what messages and imagery appeal to different people to create that real-time personalized experience.

But the problem only begins there! The other current challenge we are faced with, is the expectation by consumers to create a personalized experiences. In the ever evolving digital evolution, consumers are more demanding than ever for personalization but they equally demanding that their information is protected.

While 73% of consumers prefer buying from companies that personalize the shopping experience for convenience, 94% are concerned about data privacy and how companies use their data. While these statistics seem conflicting, there are methods to deliver a balance of relevancy and privacy to consumers. “Marketers shouldn’t have to select between relevancy OR privacy, but rather relevancy AND privacy.”

So what’s a marketer to do?

Tweet Quote: “Marketers shouldn’t have to select between relevancy OR privacy, but rather, relevancy AND privacy”

 

Diggen is the middleware. Think of it as the relationship coach in a really bad tug-of-war between partners. Marketers are using more tools and technology to help tailor the experience for customers, but in order to tailor those experiences they need data. There are many data providers out there focused on collecting the data but aren’t necessarily concerned with how the data is being used (which then causes mistrust from the customer). Diggen is the middleman by securely brokering the deal between data providers and the applications using the data. Diggen provides the security customers want, while vetting the data that CRM tools actually need which will then allow businesses to create the personalized marketing experiences that matter.

 

Sources:

http://www.fluiddrivemedia.com/advertising/marketing-messages/

http://www.emarketer.com/Article/Marketers-Stuck-on-Basic-Data-Personalization/1012763

http://www.dmnews.com/marketing-strategy/drizly-chugs-down-data-to-drive-personalization/article/428643/

http://venturebeat.com/2015/07/22/80-of-consumers-have-updated-their-privacy-settings-and-other-barriers-to-personalization/

http://insight.venturebeat.com/state-of-marketing-technology-hyper-personalization?utm_source=vb&utm_medium=refer&utm_content=editorial-post&utm_campaign=somt-personalization-report

http://insight.venturebeat.com/state-of-marketing-technology-hyper-personalization?utm_source=vb&utm_medium=refer&utm_content=editorial-post&utm_campaign=somt-personalization-report

http://0ca36445185fb449d582-f6ffa6baf5dd4144ff990b4132ba0c4d.r41.cf1.rackcdn.com/Make%20It%20Personalized.jpg

https://uploads.www.gigya.com/2015/07/16143453/Gigya_Infographic_2015PrivacyPersonalization.jpg